This article focuses on the technology, performance, and future planning of StarRocks' blazing-fast data lake analytics.
This article describes how to optimize the performance of the product features provided by the Enterprise Edition to help you efficiently access lake houses.
This article aims to solve the performance problems of offline data warehouses (daily and hourly) during production and usage.
This article reveals the key technologies of the data lake analytics engine in detail and uses StarRocks to help users understand the architecture of the system.
This article shares the application practice of Weimiao based on the big data ecosystem of Alibaba Cloud.
A guide to configure integration between Alibaba Cloud EMR with Active Directory.
Big Data is among the biggest IT trends of the last years. Maintaining a large infrastructure for analytics is a major challenge for Big Data.
In this article, we will discuss about Spark for big data and show you how to set it up on Alibaba Cloud.
This article discusses the practices and challenges of EMR Spark on Alibaba Cloud Kubernetes.
This article explains the background of Delta Lake along with practices, problems, and solutions.
This article reviews JindoFS stress testing, featuring multiple scenarios and graphs.
This article introduces Fluid, an open source Kubernetes-native distributed dataset orchestrator and accelerator for data-intensive applications, and talks about the advantages of JindoRuntime.
This article introduces the establishment of a cloud-native data lake system based on Alibaba Cloud OSS, Data Lake Formation (DLF), and various computing engines present in Alibaba Cloud.
This article explains how to perform real-time CDC synchronization in a data lake using Alibaba Cloud's Data Lake Formation (DLF) service.
This article discusses the data lake offline data migration process using JindoDistCp and explains how it improves the migration performance in different scenarios.
The article briefly discusses Alibaba Cloud's JindoTable and explains how it solves the data management problems in a data lake.
This article explains some of the challenges in cloud-native compute engines, and discusses some solutions and future directions.
This article briefly discusses the metadata service and multi-engine support capabilities of the Alibaba Cloud Data Lake Formation (DLF) service.
This article discusses Alibaba Cloud's EMR Remote Shuffle Service and explains how it solves the shuffle stability problems in compute-storage separation architectures.
This article explains the benefits, architecture, and implementation challenges of data lake metadata services.
